María Martin

36.2k total citations · 2 hit papers
81 papers, 4.3k citations indexed

About

María Martin is a scholar working on Molecular Biology, Spectroscopy and Genetics. According to data from OpenAlex, María Martin has authored 81 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 17 papers in Spectroscopy and 8 papers in Genetics. Recurrent topics in María Martin's work include Genomics and Phylogenetic Studies (36 papers), Bioinformatics and Genomic Networks (20 papers) and Machine Learning in Bioinformatics (18 papers). María Martin is often cited by papers focused on Genomics and Phylogenetic Studies (36 papers), Bioinformatics and Genomic Networks (20 papers) and Machine Learning in Bioinformatics (18 papers). María Martin collaborates with scholars based in United Kingdom, United States and Spain. María Martin's co-authors include Claire O’Donovan, Tunca Doğan, Rengül Çetin-Atalay, Ahmet Süreyya Rifaioğlu, Volkan Atalay, Sangya Pundir, Tony Sawford, Rachael P. Huntley, Johannes Söding and Milot Mirdita and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

María Martin

81 papers receiving 4.3k citations

Hit Papers

Uniclust databases of clu... 2016 2026 2019 2022 2016 2018 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
María Martin United Kingdom 28 3.1k 842 433 394 328 81 4.3k
Ram Samudrala United States 38 3.2k 1.0× 831 1.0× 898 2.1× 422 1.1× 384 1.2× 127 4.7k
Mona Singh United States 34 4.1k 1.3× 653 0.8× 327 0.8× 592 1.5× 295 0.9× 126 5.3k
Sameer Velankar United Kingdom 27 3.6k 1.1× 723 0.9× 845 2.0× 443 1.1× 219 0.7× 69 4.5k
Francisco Melo Chile 26 4.0k 1.3× 501 0.6× 963 2.2× 396 1.0× 260 0.8× 70 5.5k
Jinn‐Moon Yang Taiwan 32 2.3k 0.7× 894 1.1× 253 0.6× 244 0.6× 358 1.1× 157 4.3k
Herman van Vlijmen Belgium 38 3.1k 1.0× 1.3k 1.6× 784 1.8× 192 0.5× 207 0.6× 98 4.3k
Michael E. Pique United States 23 2.6k 0.8× 713 0.8× 441 1.0× 573 1.5× 258 0.8× 34 4.3k
Zhenling Peng China 29 3.5k 1.1× 446 0.5× 725 1.7× 195 0.5× 166 0.5× 60 4.1k
Kentaro Tomii Japan 27 2.9k 0.9× 530 0.6× 368 0.8× 274 0.7× 244 0.7× 77 3.9k
Jaime Prilusky Israel 25 3.9k 1.3× 438 0.5× 859 2.0× 342 0.9× 185 0.6× 40 5.0k

Countries citing papers authored by María Martin

Since Specialization
Citations

This map shows the geographic impact of María Martin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by María Martin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites María Martin more than expected).

Fields of papers citing papers by María Martin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María Martin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by María Martin. The network helps show where María Martin may publish in the future.

Co-authorship network of co-authors of María Martin

This figure shows the co-authorship network connecting the top 25 collaborators of María Martin. A scholar is included among the top collaborators of María Martin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with María Martin. María Martin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Insana, Giuseppe, María Martin, & William R. Pearson. (2024). Improved selection of canonical proteins for reference proteomes. NAR Genomics and Bioinformatics. 6(2). lqae066–lqae066. 2 indexed citations
2.
Rifaioğlu, Ahmet Süreyya, María Martin, Rengül Çetin-Atalay, et al.. (2023). Transfer learning for drug–target interaction prediction. Bioinformatics. 39(Supplement_1). i103–i110. 35 indexed citations
3.
Bowler-Barnett, Emily, Jun Fan, Jie Luo, et al.. (2023). UniProt and Mass Spectrometry-Based Proteomics—A 2-Way Working Relationship. Molecular & Cellular Proteomics. 22(8). 100591–100591. 16 indexed citations
4.
Owen, Gareth, Paul Thiessen, Tiejun Cheng, et al.. (2021). Enhancing the interoperability of glycan data flow between ChEBI, PubChem, and GlyGen. Glycobiology. 31(11). 1510–1519. 6 indexed citations
5.
Doğan, Tunca, Heval Ataş, Vishal Joshi, et al.. (2021). CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations. Nucleic Acids Research. 49(16). e96–e96. 26 indexed citations
6.
Martin, María, et al.. (2020). Effect of sequence padding on the performance of deep learning models in archaeal protein functional prediction. Scientific Reports. 10(1). 14634–14634. 33 indexed citations
7.
McGarvey, Peter B., Andrew Nightingale, Jie Luo, et al.. (2019). UniProt genomic mapping for deciphering functional effects of missense variants. Human Mutation. 40(6). 694–705. 28 indexed citations
8.
Huntley, Rachael P., Barbara Kramarz, Tony Sawford, et al.. (2018). Expanding the horizons of microRNA bioinformatics. RNA. 24(8). 1005–1017. 26 indexed citations
9.
LeDuc, Richard D., Veit Schwämmle, Michael R. Shortreed, et al.. (2018). ProForma: A Standard Proteoform Notation. Journal of Proteome Research. 17(3). 1321–1325. 28 indexed citations
10.
Kramarz, Barbara, Paola Roncaglia, Birgit Meldal, et al.. (2018). Improving the Gene Ontology Resource to Facilitate More Informative Analysis and Interpretation of Alzheimer’s Disease Data. Genes. 9(12). 593–593. 9 indexed citations
11.
Bursteinas, Borisas, Ramona Britto, Benoît Bely, et al.. (2016). Minimizing proteome redundancy in the UniProt Knowledgebase. Database. 2016. baw139–baw139. 16 indexed citations
12.
Courtot, Mélanie, Aleksandra Shypitsyna, Elena Speretta, et al.. (2015). UniProt-GOA: A Central Resource for Data Integration and GO Annotation.. 227–228. 4 indexed citations
13.
Huntley, Rachael P., Tony Sawford, Prudence Mutowo, et al.. (2014). The GOA database: Gene Ontology annotation updates for 2015. Nucleic Acids Research. 43(D1). D1057–D1063. 414 indexed citations
14.
Salazar, Gustavo A, Leyla García, Philip Jones, et al.. (2012). MyDas, an Extensible Java DAS Server. PLoS ONE. 7(9). e44180–e44180. 1 indexed citations
15.
Griss, Johannes, María Martin, Claire O’Donovan, et al.. (2011). Consequences of the discontinuation of the International Protein Index (IPI) database and its substitution by the UniProtKB “complete proteome” sets. PROTEOMICS. 11(22). 4434–4438. 24 indexed citations
16.
Alam-Faruque, Yasmin, Rachael P. Huntley, Varsha Khodiyar, et al.. (2011). The Impact of Focused Gene Ontology Curation of Specific Mammalian Systems. PLoS ONE. 6(12). e27541–e27541. 20 indexed citations
17.
Hermjakob, Henning, et al.. (1998). SPTR - A comprehensive, non-redundant and up-to-date view of the protein sequence world.. 3 indexed citations
18.
Martin, María, José I. Núñez, Francisco Sobrino, & Joaquı́n Dopazo. (1998). A procedure for detecting selection in highly variable viral genomes: evidence of positive selection in antigenic regions of capsid protein VP1 of foot-and-mouth disease virus. Journal of Virological Methods. 74(2). 215–221. 19 indexed citations
19.
Olivares, Isabel, et al.. (1995). Sequence analysis of HIV-1vif gene in Spanish isolates. Virus Genes. 9(3). 283–288. 2 indexed citations
20.
Sánchez‐Palomino, Sonsoles, Joaquı́n Dopazo, Isabel Olivares, María Martin, & Cecilio López‐Galíndez. (1995). Primary genetic characterization of HIV-1 isolates from WHO-sponsored vaccine evaluation sites by the RNase-A mismatch method. Virus Research. 39(2-3). 251–259. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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